Planning Inspection Paths Through Evolutionary Multi-Objective Optimization


We propose a new method for planning paths allowing the inspection of complex 3D structures, given a triangular mesh model of the structure. The method differs from previous approaches in its emphasis on generating and considering also plans that result in imperfect coverage of the inspection target. In many practical tasks, one would accept imperfections in coverage if this results in a substantially more energy efficient inspection path. We therefore apply an evolutionary multi-objective optimization algorithm to the problem -- which generates a set of solutions exploring the different ways to balance energy usage and coverage degree. To our knowledge, this is the first work that exploits the power of multiobjective evolution to explore the set of inspection plans that result in the most energy-efficient coverage of structures. The performance of the optimizer is demonstrated on a model of a subsea oilfield installation -- a type of structure that has many occluded and hidden parts, and that therefore illustrates the need for a method accepting imperfectly covering solutions.